{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Matplotlib　[官网](https://matplotlib.org/users/pyplot_tutorial.html)\n",
    "\n",
    "Matplotlib的设计理念是能够用轻松简单的方式生成强大的可视化效果，是Python学习过程中核心库之一。\n",
    "\n",
    "用在python中绘制数组的2D图形库\n",
    "\n",
    "matplotlib代码在概念上分为3个部分：\n",
    "\n",
    "1.pylab接口是由matplotlib.pylab提供的函数集，允许用户使用非常类似于MATLAB图生成代码的代码创建绘图\n",
    "\n",
    "2.matplotlib前端或API是一组重要的类，可创建和管理图形，文本，线条，图表等（艺术家教程），是一个对输出无所了解的抽象接口\n",
    "\n",
    "3.后端是设备相关的绘图设备，也称为渲染器，将前端表示转换为打印件或显示设备；后端示例：PS 创建 PostScript® 打印件，SVG 创建可缩放矢量图形打印件，Agg 使用 Matplotlib 附带的高质量反颗粒几何库创建 PNG 输出，GTK 在 Gtk+ 应用程序中嵌入 Matplotlib，GTKAgg 使用反颗粒渲染器创建图形并将其嵌入到 Gtk+ 应用程序中，以及用于 PDF，WxWidgets，Tkinter 等\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.mlab as mlab\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 例子１\n",
    "\n",
    "def simple_plot():\n",
    "    # 生成测试数据\n",
    "    x = np.linspace(-np.pi, np.pi, 256, endpoint=True)\n",
    "    y_cos, y_sin = np.cos(x), np.sin(x)\n",
    "\n",
    "    # 生成画布，并设定标题\n",
    "    # 画布大小，dpi＝清晰度\n",
    "    plt.figure(figsize=(8, 6), dpi=80)\n",
    "    plt.title(\"Simple plot\")\n",
    "    plt.grid(True)  # 带网格\n",
    "\n",
    "    # 设置X轴\n",
    "    plt.xlabel(\"X\")\n",
    "    plt.xlim(-4.0, 4.0)\n",
    "    plt.xticks(np.linspace(-4, 4, 9, endpoint=True))\n",
    "\n",
    "    # 设置Y轴\n",
    "    plt.ylabel(\"Y\")\n",
    "    plt.ylim(-1.0, 1.0)\n",
    "    plt.yticks(np.linspace(-1, 1, 9, endpoint=True))\n",
    "\n",
    "    # 画两条曲线\n",
    "    plt.plot(x, y_cos, \"b--\", linewidth=2.0, label=\"cos\")\n",
    "    plt.plot(x, y_sin, \"g-\", linewidth=2.0, label=\"sin\")\n",
    "\n",
    "    # 设置图例位置,loc可以为[upper, lower, left, right, center]\n",
    "    plt.legend(loc=\"upper left\",shadow=True) \n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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I2SOMWDXCdBzhA0FT8AghglOOHNCihekU9vLww1CkCJzLOMsnyz8G4Il6T5A3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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdbdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simple_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 更复杂一点\n",
    "def simple_advanced_plot():\n",
    "    \"\"\"\n",
    "    simple advanced plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    x = np.linspace(-np.pi, np.pi, 256, endpoint=True)\n",
    "    y_cos, y_sin = np.cos(x), np.sin(x)\n",
    "\n",
    "    # 生成画布, 并设定标题\n",
    "    plt.figure(figsize=(8, 6), dpi=80)\n",
    "    plt.title(\"simple advanced plot\")\n",
    "    plt.grid(True)\n",
    "\n",
    "    # 画图的另外一种方式\n",
    "    ax_1 = plt.subplot(111) # 也可以写成plt.subplot(1,1,1)\n",
    "    ax_1.plot(x, y_cos, color=\"blue\", linewidth=2.0, linestyle=\"--\", label=\"left cos\")\n",
    "    ax_1.legend(loc=\"upper left\", shadow=True)\n",
    "\n",
    "    # 设置Y轴(左边)\n",
    "    ax_1.set_ylabel(\"left cos y\")\n",
    "    ax_1.set_ylim(-1.0, 1.0)\n",
    "    ax_1.set_yticks(np.linspace(-1, 1, 9, endpoint=True))\n",
    "\n",
    "    # 画图的另外一种方式\n",
    "    ax_2 = ax_1.twinx()\n",
    "    ax_2.plot(x, y_sin, color=\"green\", linewidth=2.0, linestyle=\"-\", label=\"right sin\")\n",
    "    ax_2.legend(loc=\"upper right\", shadow=True)\n",
    "\n",
    "    # 设置Y轴(右边)\n",
    "    ax_2.set_ylabel(\"right sin y\")\n",
    "    ax_2.set_ylim(-2.0, 2.0)\n",
    "    ax_2.set_yticks(np.linspace(-2, 2, 9, endpoint=True))\n",
    "\n",
    "    # 设置X轴(共同)\n",
    "    ax_1.set_xlabel(\"x\")\n",
    "    ax_1.set_xlim(-4.0, 4.0)\n",
    "    ax_1.set_xticks(np.linspace(-4, 4, 9, endpoint=True))\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QAKpWtab1rJpSwUELNaWCmNMJn35qTbdpA6F6e5FPE7l6Vm3KFDh61N48SqnM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\niJmlmNnx2davA353zm0IZ7hoKNQGA78QnCWbRXDaci6AmZ1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/HoqpQ7QchHNuIYCZtcjF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\nREREJEqpUBMRERGJUirURERERKLU/wPzdRtXT95a4AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x839cc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simple_advanced_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 练习把上面的图，改一下线段颜色和形式， 如：red, yellow, ; -."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 一次画多个图\n",
    "def subplot_plot():\n",
    "    \"\"\"\n",
    "    subplot plot\n",
    "    \"\"\"\n",
    "    # 子图的style列表\n",
    "    style_list = [\"g+-\", \"r*-\", \"b.-\", \"yo-\"]\n",
    "    \n",
    "    plt.figure(figsize=(8, 6), dpi=80)\n",
    "\n",
    "    # 依次画图\n",
    "    for num in range(4):\n",
    "        # 生成测试数据\n",
    "        x = np.linspace(0.0, 2+num, num=10*(num+1))\n",
    "        y = np.sin((5-num) * np.pi * x)\n",
    "\n",
    "        # 子图的生成方式\n",
    "        plt.subplot(2, 2, num+1)\n",
    "        plt.title(\"sub plot %d\" % (num+1))\n",
    "        plt.plot(x, y, style_list[num])\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EwdmsWTV2FibT03PeFKNZKExEAqwK55zJww/z69tu49dm992JEyVMLGbPgT3Ivzcff/X0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UchhMOirjJCCGQyQyCKeeo+akQiwbb0hYI7W/pSKYt8fgzJ5KDilVlYBbDuCokLhamyC7ERJoHg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x82e9588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "subplot_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 柱状图\n",
    "def bar_plot():\n",
    "    \"\"\"\n",
    "    bar plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    means_men = (20, 35, 30, 35, 27)\n",
    "    means_women = (25, 32, 34, 20, 25)\n",
    "\n",
    "    # 设置标题\n",
    "    plt.title(\"bar plot\")\n",
    "\n",
    "    # 设置相关参数\n",
    "    index = np.arange(len(means_men))\n",
    "    bar_width = 0.35\n",
    "\n",
    "    # 画柱状图\n",
    "    plt.bar(index, means_men, width=bar_width, alpha=0.2, color=\"b\", label=\"boy\")\n",
    "    plt.bar(index+bar_width, means_women, width=bar_width, alpha=0.8, color=\"r\", label=\"lady\")\n",
    "    plt.legend(loc=\"upper right\",shadow=True)\n",
    "\n",
    "    # 设置柱状图标示\n",
    "    for x, y in zip(index, means_men):\n",
    "        plt.text(x, y+0.3, y, ha=\"center\", va=\"bottom\")\n",
    "    for x, y in zip(index, means_women):\n",
    "        plt.text(x+bar_width, y+0.3, y, ha=\"center\", va=\"bottom\")\n",
    "\n",
    "    # 设置刻度范围/坐标轴名称等\n",
    "    plt.ylim(0, 45)\n",
    "    plt.xlabel(\"Group\")\n",
    "    plt.ylabel(\"Scores\")\n",
    "    plt.xticks(index+(bar_width/2), (\"A\", \"B\", \"C\", \"D\", \"E\"))\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bar_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 横向柱状图\n",
    "def barh_plot():\n",
    "    \"\"\"\n",
    "    barh plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    means_men = (20, 35, 30, 35, 27)\n",
    "    means_women = (25, 32, 34, 20, 25)\n",
    "\n",
    "    # 设置标题\n",
    "    plt.title(\"barh plot\")\n",
    "\n",
    "    # 设置相关参数\n",
    "    index = np.arange(len(means_men))\n",
    "    bar_height = 0.35\n",
    "\n",
    "    # 画柱状图(水平方向)\n",
    "    plt.barh(index, means_men, height=bar_height, alpha=0.2, color=\"b\", label=\"Men\")\n",
    "    plt.barh(index+bar_height, means_women, height=bar_height, alpha=0.8, color=\"r\", label=\"Women\")\n",
    "    plt.legend(loc=\"upper right\", shadow=True)\n",
    "\n",
    "    # 设置柱状图标示\n",
    "    for x, y in zip(index, means_men):\n",
    "        plt.text(y+0.3, x, y, ha=\"left\", va=\"center\")\n",
    "    for x, y in zip(index, means_women):\n",
    "        plt.text(y+0.3, x+bar_height, y, ha=\"left\", va=\"center\")\n",
    "\n",
    "    # 设置刻度范围/坐标轴名称等\n",
    "    plt.xlim(0, 45)\n",
    "    plt.xlabel(\"Scores\")\n",
    "    plt.ylabel(\"Group\")\n",
    "    plt.yticks(index+(bar_height/2), (\"A\", \"B\", \"C\", \"D\", \"E\"))\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barh_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 层次柱状图\n",
    "def table_plot():\n",
    "    \"\"\"\n",
    "    table plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    data = np.array([\n",
    "        [1, 4, 2, 5, 2],\n",
    "        [2, 1, 1, 3, 6],\n",
    "        [5, 3, 6, 4, 1]\n",
    "    ])\n",
    "\n",
    "    # 设置标题\n",
    "    plt.title(\"table plot\")\n",
    "\n",
    "    # 设置相关参数\n",
    "    index = np.arange(len(data[0]))\n",
    "    color_index = [\"r\", \"g\", \"b\"]\n",
    "\n",
    "    # 声明底部位置\n",
    "    bottom = np.array([0, 0, 0, 0, 0])\n",
    "\n",
    "    # 依次画图,并更新底部位置\n",
    "    for i in range(len(data)):\n",
    "        plt.bar(index, data[i], width=0.5, color=color_index[i], bottom=bottom, alpha=0.7, label=\"label %d\" % i)\n",
    "        bottom += data[i]\n",
    "\n",
    "    # 设置图例位置\n",
    "    plt.legend(loc=\"upper left\", shadow=True)\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 饼图\n",
    "def pie_plot():\n",
    "    \"\"\"\n",
    "    pie plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    sizes = [15, 30, 45, 10]\n",
    "    labels = [\"Frogs\", \"Cat\", \"Dogs\", \"Logs\"]\n",
    "    colors = [\"yellowgreen\", \"gold\", \"lightskyblue\", \"lightcoral\"]\n",
    "\n",
    "    # 设置标题\n",
    "    plt.title(\"pie\")\n",
    "\n",
    "    # 设置突出参数\n",
    "    explode = [0, 0.05, 0, 0]\n",
    "\n",
    "    # 画饼状图\n",
    "    patches, l_text, p_text = plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct=\"%1.1f%%\", shadow=True, startangle=90)\n",
    "\n",
    "    plt.axis(\"equal\")\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return\n",
    "# pie_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pie_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 散点图\n",
    "def scatter_plot():\n",
    "    \"\"\"\n",
    "    scatter plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    point_count = 1000\n",
    "    x_index = np.random.random(point_count)\n",
    "    y_index = np.random.random(point_count)\n",
    "\n",
    "    # 设置标题\n",
    "    plt.title(\"scatter\")\n",
    "\n",
    "    # 设置相关参数\n",
    "    color_list = np.random.random(point_count)\n",
    "    scale_list = np.random.random(point_count) * 100\n",
    "\n",
    "    # 画散点图\n",
    "    plt.scatter(x_index, y_index, s=scale_list, c=color_list, marker=\"o\")\n",
    "\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return\n",
    "# scatter_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "scatter_plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 雷达图\n",
    "def radar_plot():\n",
    "    \"\"\"\n",
    "    radar plot\n",
    "    \"\"\"\n",
    "    # 生成测试数据\n",
    "    labels = np.array([\"A\", \"B\", \"C\", \"D\", \"E\", \"F\"])\n",
    "    data = np.array([68, 83, 90, 77, 89, 73])\n",
    "    theta = np.linspace(0, 2*np.pi, len(data), endpoint=False)\n",
    "\n",
    "    # 数据预处理\n",
    "    data = np.concatenate((data, [data[0]]))\n",
    "    theta = np.concatenate((theta, [theta[0]]))\n",
    "\n",
    "    # 画图方式\n",
    "    plt.subplot(111, polar=True)\n",
    "    plt.title(\"radar\")\n",
    "\n",
    "    # 设置\"theta grid\"/\"radar grid\"\n",
    "    plt.thetagrids(theta*(180/np.pi), labels=labels)\n",
    "    plt.rgrids(np.arange(20, 100, 20), labels=np.arange(20, 100, 20), angle=0)\n",
    "    plt.ylim(0, 100)\n",
    "\n",
    "    # 画雷达图,并填充雷达图内部区域\n",
    "    plt.plot(theta, data, \"bo-\", linewidth=2)\n",
    "    plt.fill(theta, data, color=\"red\", alpha=0.25)\n",
    "    \n",
    "    # 保存图片\n",
    "    plt.savefig('radar.png')\n",
    "    # 图形显示\n",
    "    plt.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xZSzsdvs1I0eOfODjjz+2Z2Vl6Tbunj3AqFGAyCuoefkL5GTJUCjFKq8Xs6xWiANEKymlqJdl7AmFwBGC4aIIJ8um7CSBUiAQYno3Mh2RLVNLe8STae2MejMRT8YbTDxgmZ2laoammyHJJcjKpiBMGxSlEfn5Zowfn4eCAnPXa7p3SFi+HLjuOsDv/+6xVJxCffDBB+pll112oKGhYTaltNa4mYYOx42xyMnJuWns2LH3ffTRR3aLxTLwG+Lgl0tV/OlBBpefUYvn7tzZ9XitJKFBljGlj4CATCkOhsPYHw7DznEYKQiwHWUanWGJaAakD0OjGZmWDg6t3u+2TG1+HpQmZgytlu/iMt/sZhEKHTlOSQlQVZXkhxuAVatW0YsuuuhgQ0PDyZTSXiJWxxbHhbHIyclZOnHixF+vXLnSbjKZdB07GAQK8xU0t7L44tFNOHFCR9dzlFKs9flQZjYjq5sRUChFVTiMA+EwCngewwQBwnGmh6EoQLuvHyMTDf5qcZmmTh7NXh7tXgGKMvDvipDItsxovvzySyxatKimvr5+LqV0r/EzDh7HvLFwOp13Tp06denbb7+dbUSHr2XLgMsuA6YMb8empzcfEexrVxRUBgKYpZWwH5Qk7AmFUMDzGCGK4IZg5uNQpk1WsKlVQqdXQE7Iih/cMRUNbUf+v6bCs4iyefNmLFy4sPbQoUPzKKW7UzNr6jmmb2e5ubm3TZkyZek777xjiKEAgH88IgMAbji/rtdTgSyWhYVhsD0YxCqfD52KgtlWK8aYTGlDkQDZHIvTnCbMKVJBChtx8zXbIIryYa+xWCKp9qli6tSpWLlyZb7b7f6UEJJcFtgQ5pj1LBwOx40TJ0787QcffGBPJtmqPyoqgMmTgQyzhNpX18FmPrKEwKeq+NrvR7uiYK7NdtTFJIYylFLsCIXw7IdOvPD8BBxqMgEg+OtfgZ//PPXrWb9+Pb7//e8frK+vP+lY7F1yTHoW2dnZV44dO/a3K1euNMxQAMA/Ho0Yh8vnHzrCUKiUYlcohA1+P8aZTBhrMqFGkgxby/GICqBekvCbhW349IXPcNrJkevT5x0cPd7p06fjlVdeKXS5XGsIIe5BWYSBHHPGwmKxfH/EiBEPfvTRR3azgWmJnZ3AsuWRbcQN59Ud9lyLLGO1zweVUpxstSKH4zBcEFAnSQikIup2nLAnFEKRIMDCshhrMuGnZ0cEiJ54IoRweHAM85w5c8iKFSuKnU7nakJIxqAswiCOKWNBCJngcrn+9eGHH9qN1sRc9gKF18fg5NJmlA6PHPKrlKIyEMA3oRCmmc0YazKB0eISDCEYbzJhe/C4SvozjICqolaSMKJbLOrcGe1wZwew/4AZTz1VgcbGwdHiPfXUU5mHHnqoxOl0vkkIOWausWPmgxBCHC6Xa+U777yTm5OTY+hclH63Bbnh/HoAgFdRsMbng4lhcJLF0mtsIo/nIVGKFlk+4rk08bE9GMS4bsYYADiWYvH8SELlls0TsWvXLmzfvh3qIHhzl156KX/ppZdOczqdD6Z8coM4JowFIYRzOp3vP/nkk554hU4S4fPPga3bObiygjh/TgMOhMPY4PdjktmMUQMIwZSaTNgWDKYl+JKgRZYRphR5HHfEc5efGTEWL7/Mobz8JHAch7Vr18Ln86V6mfjTn/6UUVZWtiQjI2OISCAlxzFhLFwu1xM33XTT+HPPPffIb48B/OORiFdx5dl12Kb40STLmGOzITuGk44MloWdZXEwHexMCEoptgWDKDOZejXKk0b6MHl4O1rbGbz7LsGYMWMwYcIErF+/HjU1qT2gYFkWr7/+uj0vL+9vhJDylE5uAEe9sXA4HD+dOXPmBXfffXdKGnc0NgKvvMaAEIqpZ+yFi+NQbrHElTMx1mTCnlAIUtq7iJtqSUI2yyKjH8O85KyId/HcvyLbPYfDgdmzZ6O6uho7duxIqVeXmZmJ999/P8ftdr9FCElMWWmIcFQbC47j5ng8nvtWrFiRlaqiq389TRGWCGZOq8f8EoqiBJK9eK1YbFcoZMAKj11kSrE7FMLYAVL2LzmjASyj4t33WURjnDzPY8aMGVBVFRs2bICcwrjRyJEj8cILL7idTueHhBDjzvIN5qg1FoSQ4ry8vFfef/99h96FYX2hqsBjj0a2D//v/Ho4etkzx0oJz6NRluFTho4WLKW015+hws5QKFJHM8CNIc8h4axpTZBlghX/+W79hBCUlpYiLy8PX3zxBQKBgNFL7uKMM85gfv3rX49yuVzLj9bu2UdlBichRHQ6nRWvv/766FmzZqXkF08pxVNP1eC66wpR4vRhz3/WI9lkzCZZxt5QCDNS0PowTCl8igKfqsKnqvCqKoKqCgn4Tg+QEPT8ZXb/fjCEQCAEFoaBtccPY/D336eq2OD342SrNaa5XvqvEz+6rxTTpsjYsPlIo97c3IyKigqUl5dDT7mC/qCU4rLLLmt/7733ftvc3PznlEyqIykJCOqNy+X602233VaUSkNRWVmJ5S8UAQCuP/dQ0oYCAHI5DvtCITTKMpxJeCk9UShFu6KgVfvpVBTwhMDGsrAyDDJZFh6eh4kQ8ITErJuhUIowpfBrBqdVUVAtSfCqKlgA2Vrw1q7Vw+h5A90WCGBCj6PS/jh3djOyLGFs/FrAtm1Az0OynJwcTJ8+HRs2bMCkSZN0leDrC0IInn766ayysrLbCSFvUkp3DvyuocNR51kQQqZPmTJl5YYNGxxsCuosKKWoqKhAfb2Is88eC5aoqH55HVx2fU4z/KqK9XHcMfvCp6pokCTUyzKCqgo7x3VdvBk6X7i9IVGKNkVBm6KgRZbhV1U4OA55HIdcjkuqaK5RlrEvAQ/s+j+NwhPvFuL2/6fijw/0vuP2+/346quvMHHiRBidnxNl48aNWLhwYWVDQ8OUo6knyVEVsyCEmFwu14svvfRSygzF5s2bwfM8Pvt0DFSV4AcnN+hmKADAwjBwcRz2h8Nxv9evqtgZDOIzrxcVgQAogIkmE07JyMBksxklgoDMFClu8YTAyXEYLYqYabVins2GfJ5Hsyxjjc+HL30+1EoSlDhvTiql2B4MojSB1P3LtVORF16g6Cs0ZLFYMHPmTFRWVqYs43PatGm4/PLLS3Jycu5IyYQ6cVR5Fi6X65Ff/vKXVy9dulRfBZteUFUVmzZtQkZGBoYNG4OSIhX1jSxW/W0zTp7UrutcMqVY7fVittU6oAiOTClqJAnVmnEpFATk8zz4IR4z61AUHJQkNEgS7ByHYp6PKUC8LxRCgFJMSEC0iFJg9CUnYM8hGz74AJg/v+/XhkIhfPnllxg7diwS7R0TD6FQCGVlZc27d++efbT0IzlqPAtCyMzCwsKLf/GLXxhuKCil2LJlCzIzMzF27Fi8/jpBfSOL0uIOzJmor6EAAI4QjBJFfNvPUWpQVbEjGMRqrxdBVcVUiwWzbTaUCMKQNxQAkMmyKDWZcIrNhgKex95wGKu9XtRIEtQ+blhhTVFsTIKVw4R8l9H53L/69/ZFUcSJJ56Ib7/9Fs3NzQnNFw+iKGLFihU5LpfrVULIUaFbcFQYC237seKll15y9NViT0927NgBjuMQVf/uErg571DCsvcDUcjzaFMUdPTwlzsVBZv8fnzl98PGMJhns2GsyQTLUSrDR7TtygkWC6ZZLGiTZXzm9WJPKHTEFuXbYBAjk1QTu0wzFq+9TtDZ2f9rBUHA9OnTsXXrVnR0dPT/Yh2YNm0alixZUuJwOH5t+GQ6cFR841wu10O333573qhRowyfa+/evfD7/SgrKwMhBNu3A5+t4WAVJVy2oN6weQkhKOtWNxLQRHO2BAIoEgScbLWiSBAMP6JMJRaGQanZjDk2G1QAq7xe7A+HoVKKTi1YWpRku8PhniDmljUjEGTw6qsDv95sNmPatGnYuHEj/N0lww3it7/9rS0nJ+fnhJBxhk+WJEPeWBBCTiwsLPzRLbfcYnjPrJqaGhw6dAhTp07tCgr+87FIxeLiM+qRaTU2cG3nOPAA1mueRB7PY7bVCifHDcku5XrBE4LRoojZNht8qopVXi82+v2YoFN39svPigQuo+nfA5GRkYHJkydj/fr1CCcQeI4HQRCi25FXhvp2ZEgbC0II53K5/p2K7UdzczP27NmD6dOnI3rS4vMBzz0fef6G8w4ZOj+lFDXhMNpVFW2KgtkWCzwpaGg8lBAIwQSTCSNEERKl2BUOw69DefmF8xph4mV8uprrtXl1bzgcDowbNw5fffWV4SXu5eXluOKKK0ocDscvDZ0oSYa0scjMzPzJkiVLnCNHjjR0nmAwiIqKCkyfPv2wDlj/+Q/Q0cngxLGtmDLKa9j8PlXFl34/GmUZJ1utGCYIqDpOq1JVSrE3FMIcmw2jRBFf+f3YFQr1GQSNhSybgvNnR7yLZS/EfuHn5eXB4/GgsrIy4blj5Te/+Y3NbDbfQghJTTppAgxZY0EIsVgsljvvuusum5HzqKqKjRs3oqysDN1l+CjtrtxtjFdBKcW+UAjr/X6MFkVMsVggMAxGiiKqw2EEj0MJvr3hMDw8DzPDIJfjcLLVCpVSrNGU0RPl8rO1rcgzalzd7keMGIFQKISDBw8mPHcsmM1m3H333dlOp/M+QydKgiFrLBwOx+2/+MUvspNpkhsL27dvh8vlgtPpPOzx9euBTVs4OGwh/PBU/ZN1wlrmZoeqdul0RmEJwRiTCTuOMwm+kKriYDiMUd2OSllCMNZkwiSzGRv9fuwPhxMqbjtjWivc2QHs2svhyy9jfx8hBFOnTsXevXvR3q7/sXl3rr76asFms11CCPEYOlGCDEljQQhxWCyWG372s58ZmlNRU1MDv9+P3k5ZogI3V519CCZB3zt8syzjc58PhYKAyWYz2F7iEh6OQ0BLoT5e2BEMYqzJ1OvvI5tlMcdmQ4ssY2MgELcWCMdSXKpJ7j33THy/U47jUF5ejs2bN0MycHvIcRz+9Kc/2fPy8oakFN+QNBYul+t39913X7berQa74/P5sGvXrsNOPqK0tAArXoo8dv0ifbcgVeEwtgeDONFqRX4/x4LRo9TKQGBIlYkbRZtWEevpJ6uTIwRTLRa4OQ5rfT744tymRdO/V7xIEK+USEZGBsaMGYOvv/7a0P+PCy64gM3NzV1ACBlt2CQJMuSMBSGkMCMj48LLL788uQP2fqCU4uuvv8akSZMOC2hGefYZimCIwYLyRowq0EfzgFKKrYEAmmQZs6xWmGM43cnUFKFqj/FgJ6UU2wIBlJnNMZ3+RD2yr3w+NMchYjNxhA9TR7ShrZ3B22/Hv878/HywLGuoPB8hBH//+98dbrf7EcMmSZAhZyzcbvdfHnzwQUMLxfbu3Yvs7Oxey5JV9bvciqhyd7JIlOJLvx8CIZjWx7ajL8aJInaGQpCPYe+iVpZhY9nDmkcPRDbL4kSrFduCQRyIIxci3pyLnkycGFENDxoYTzrttNPI8OHDpxFCphk2SQIMKWNBCBnncrlOPffccw1bl9frRXV1NcaN6z1h7pNPgF17WRTm+HHOScnXCEiUYp3Ph0Kex9g+RGb7Q2QYFAsCdh+jEnwKpdgZDGJcAvUfZobBLKsVdVqz6Vi4+PSI5N57H7BoaIh7SvA8j9LSUmzZssXQ7cijjz6a43a7/2nYBAkwpIyF2+1+7NFHH80xKhGp+/ajL88lGti89pxD4NjkvgwhVcUXPh9GiSIKk2jMPFwQcEjTiDjW2B0KoVgQICaYdMcRgukWC1pkGTtjuNvnOSScfcKRknvx4HK5IIqiocepU6dOxQknnDCCZdnTDZskToaMsSCEjCsuLp44Z84cw+bYu3cvHA4H7HZ7r8/X1ABvvM2AZVRcc05ygc2gqmKd349xoghPkvUNDCGYIIrHXDezgKqiTpYxPMkO9wwhmGaxoFNV8U0MPVm+y7lI/KSptLQUe/bsQchAj+/BBx905OXl/cmwCeJkyBgLt9t91913322YVFEoFMKBAwcwZsyYPl/z1JMqFIXgvFkNyM9NvCYgGqOYYDLBlaShiOLieSiUxhXQG+psDwYxXhR1KY5jCEG52Qy/qg6omv79Wc3ItoaxaQuHRJMzeZ7H2LFwzB42AAAgAElEQVRjsWPHjsQGiIExY8ZgxIgRRYSQMsMmiYMhYSwIIdmiKC5YuHChYYUQ33zzDcaMGQOuj6M5WQaefCJyR0qmDkShFF/5fBgjirrqagLGdDOjlCKoquhUFDTLMuolqeunQZa7jjT1DrC2yDIkSpGnkzEFIicJU8xmtCpKv0FPk6DiR6dEAhbPP5v41s7j8cDn8xmarHXPPffkut3uewybIA6GhGCv3W7/6S233JJpVLFYe3s7vF4vJk2a1Odr3noLqKljMbagE6eVtyU0D6UUG/1+FAhC0luP3rCxLHJYFgckCSUJuO4hrUitVVHQrihdHd1FhoGgifd2146glELSRHrDlEKmFCwhsDJMRJiX45CZgLJ3tKvYFAO63Ee3JOt8PoiE9GmMLj+rAY+/U4hlyyj+cD8SEmAmhKCsrAyVlZWYNWuWIUV/8+fPh9lsPoUQkkMpNV6Vpx8G3VgQQti8vLwbr776akOar0SVuUtLS/v9z4zUgXD4yaLEBW4qg0FksiyGJbkH748xJhPWeL0xSelRStGiKKiXZTTKMlhEyuDtLItiQYA5DmXvKDKl8KoqWrU2Bh2KArOmI+rWajoG4qAkRYSEDToe5wjBDIsFX/j9EBmm17aSJ5V2YJTHi911Nnz8MbBgQWJzZWVlwWazoba2FgUFBUmu/EgIIbjtttuy7rnnnpsB/I/uE8TBUNiGnPm9733PkpGRYcjgdXV1sFqtyM7O7vM1u3YBH37CwSzIWHJWYrkV0cKvsQlKwMUKTwhGiGK/kf8ORcG2QACfer04GA7DzrKYZbVijs2GUpMJ+TyfsFQ/RwiyWRbDRRHlFgtOychAqckECmCT34/PNQGbvtKxJUqxJ4auYskiMAymmc342u9HuJdTpHgk9wZi3Lhx2LlzJxSDUvOvuOIKQRCEqwkhg3q9DrqxyM/Pv+OWW27p+0pOAkopdu3ahbFjx/b7umgS1o9PrYc9I/4AYoeiYE84jCkWS0r0J4p5Hs2KAm+3LyelFPWShLU+H7YHg7BzHObabJii6WIYqdNpY1mM0MRrplosCKkq1ni9qAwEjjju3RUKYbgopkQ31MayGGsyYVMfKfNRyb3/e4MgGRU9URSRn59v2FGq1WrF/PnzLQAG9Rh1UI0FIcSTnZ09duLEiYaMf+jQIWRnZx9Wet6TQAB45pnI3xMJbEqUYpPfj3KzOWXCuYSQw4KddZKEVT4fDskyJplMXXUn8WSK6oWFYTBGE+Z1cBw2+v3Y5PdHGhMpCppkGSUGxHP6wsPzyGLZXsWQh7mDmKdJ7r3ySnLzjBgxAvv27TNMKOeWW26xFxQUDGrrgEE1Fg6H48Zbbrml96SHJKGUYvfu3V2iu33x0ktAazuDaaPaMH3cAIquvVARCGC0KBq2/+6LHI6DQin+6/WiXpYxw2LBZLMZthSvoy8IIcjnecyxWlHA81jv92OtdkqUavWvcaKIFu20pyfRnIvnn0nuSJrnebjdbsO8i/Lyclit1jJCiMuQCWJg0IwFIYTwPH/lxRdfbEiQtaGhATabDQM1Te6u3B0vtZIECqDAwIBmb0iUYksgABUABTDJZIopsDgYEO1EYpwoQmAY7AgGI7+3FNa6RI9UtwYCRxwBXzivEWZBxmdrOFRVJTeP0d7FzTffnG232683ZPAYGMxvWPnMmTNFm01/IaxorGIgr2LzZuDLDRyyLGH8+LT4CgVCqopvg0FMMjhQ15MGScIarxcOlsVs7a5dZbCobLKolOKbUAjTLRbMtlpRL0lY30fg0SgsDIPhvWTBZlq/k9x74fnk1iOKIpxOp2FVqZdccglvMpkuN2TwGBg0Y5Gbm3vx4sWLDcnYbG1thclkwkCGKFoHsuTMeljN8X1RKoJBjDOZBuwgpheqVsa9JxzGSVpbAKI1J9ofDqf0wouX/eEwXBwHC8NAYBhMtVhQJAj43OdDUwozUot5Hn5VRWOPOaM6F88/G5/kXm+MHDkS+/btM8RzstvtyMvLyyKE5Os+eAwMmrHgOO78s846y5DNa1VVFYYNG9bva9rbgeX/iUx/w3l1cY3foOlLGJF41RvRgjSBYXCixQJTNwPFaTL63wzRqtSwqqIqHMboHkfKHp7HiVYrvg0GsScUSsm2hBCCyWYztgWDhwkAnzGtFR57ALv3cVi3Lrk5TCYTzGYz2toSS+wbiMWLF2daLJZFhgw+AINiLAghRUVFRRlG6GuGw2F0dHQM2BH7hecp/AEGp05qwrji2JvJqJRieyiE0hRtPzoVpatydXQfwcECnkdHL93MhgLfhEIY1UdXMTPD4CSrFR2KgooeF7BRmBkGHo7Dvm5bN5ZFwpJ7vTFs2DBUJRsA6YPzzz9ftNvtSwwZfAAGxVjYbLYLFi9ebIjk+cGDB1FUVNRvxJ1S4B+PRr4U8QrcVIXDcGsutdG0yjI2+P0ot1j6raEghKDMbEalznUjyRI1YIX9rJ3Rgo8WhsF6vz/uLuuJMEoUcSAcRqjb1i26FXnxRYJki3tzc3PR3t5uiF7nyJEjwfP8CEJI/5F7AxgUY5GVlXXZeeedp/sRAqW0y1j0x+rVwPZvObizgzhvTlPM44dVFft7qE8bRYssY0sggJlWKzJjOA7NZlmYCcGhIVKVGq3/KI1B8IdoWykXx+Erv99wVTCWEIzpsXUrG+5D+cg2tHUweOut5MYnhKCwsNCwY9RFixaJAM4wZPB+SLmxIIRkmM3m4pKSEt3HbmlpQUZGBoQBjjIfezjiVVzzvTrwXOxfzD3hMEYk2ag3FtoUBRWaoYjHgxlvMuHbYDAld+eBqJdliITAHkfl7XBRRL6Wk2H0liRf27r5D/Mu9Mm5AIDi4mLDjMUPf/jDzIKCgisMGbwfUm4sGIZZcP755xvSt7SmpmZAr6K+HnjtDQYMUXHdubHnVkiU4pAkJd2odyB8ioLNfj+mxyjq2x0Tw6BAELB3kI9SFUrxTTCICQnEdUoEAU6Ow9cGq5pHT5K6a19cfHoDODZxyb3uCIIAk8lkSDf2mTNnQlGUWamuFUm5sfB4PFdedNFFuidXUErR1NSE3Nzcfl/39FMqJIngnJmNKHLFfoKwNxTCcIO7mIcpxXq/H1MtFlgTjImMEATUDHI3s73hMPJ5/rBTm3gYJYoQCDH8hMfNcWjrVqrvsks4+4RGKArBv5cnb6jy8/NRVxffSVsssCyL2bNncwCm6z54P6TUWBBCWFVVp0+bpr9ocWtrK+x2O/rTxFAU4PF/agI3cQQ2JUpRK0koMjBTk2o1JmNNpl5LqmMl2sFrsCT4gqqKmnAYI5OM65SaTGhXFNQZ2AYhGivpLoZ8+dmRGNbzzyZ/KuJ2u3HokDGtLy+++GKH0+m8xJDB+yDVnsXEGTNmMEaI3NTW1sLj6b/r23vvAQeqWYzI82HBCS0xj10dDqNIEAwtzNoZCiGTZXXJ3XBzHEKUonUQgp39dRWLB6LJ5H0bDB5WXas3Ho5Ds6baBQDfP6kJ2dYwNldw2Lo1ubF5nocoivD5fDqs9HDmz59POI47W/eB+yGlxoLjuBPmzZun+5EppRSNjY1H9CvtSbQO5PpFhxCrvaKU4oDBsYoWTZxmvE6nLD2rUlNFm6IgQCncOskJCgyDyWazofELQggKBAHVWpxHFCh+fGrykntRPB4Pamtrkx6nJ5mZmeB5PpsQkjIBq5QaC7fbfcaMGTN0v+ra29uRkZHRp7w/AOzbB7z3AQuRV3DVwthdw1ZFgY1hEpaqHwiFUlRoEnN6VmNmsiwyWRY1KepmRilFZSCAsgR6o/SHneOQw3HYbWDQtpjncbBbcduSsyPGYtkyimSdM4/HY9hWRJN2GG/I4L2QUmOhKMq0KVOm6D5uU1MTXK7+K3ef+KcKSgkumluP3KzYL6CqcNhQmbxvQyEU87whpeXjtGh/KrqZ1UgSMjQDpTdjRRG1kmTYdkRkGFgYpqsJ9czxHRjt8eJQA4uPPkpubEEQIlqmBhjtefPmZbEse4LuA/dByowFIYQXRTHTarXqPvZApyChEPD00/Erd8uUokNR4DBIIyIqBpNs34y+EBgGJYLQrzQ+pRQ+VcUhravXN8EgKgMBbAsG8W0wiP3hcJcSd1/IlGJXKKTbNqonjNYkepuBQdsSQcAB7YImpFtxmQ7p3zk5OWhpiT1GFiszZswQ3G53ytSzUulZTJg0aZLuEUJKKQKBQL+6Fa+9BjQ2s5g0rB0nlcZ+7t0gy3DxvGFiLZVaLoKRYjDDBAENPbqZqZq61ia/H59q8nctigKeEGSxLPJ4Hk5NUFehFAclCet8Pqz2erEjGERnjzv87lAIJYJgaAVuDseBJaSriE/38VkWLbLctRW5bEHktCxZyT0gkv7d1BR7pnCsTJ06Faqqpuz4NGXBES24qbvWZnt7O7Ky+o+ZPvZwRLn7hvPiU+6ulSTDUrtbtM1wrs69RXrCEIIJ2l15itmMPaEQ6iQJTo7DcEFANsvGbKwkStEgy9gWDEKmFKNEERkMg3pZxskGeIw9mWAyYYPfDyfH6W5gGUJgZ1m0KApyOA4l7hBOmdiMT7fm4OWXgauvTnxsh8OBnTt36rdYje5BTkqp4UdfKfMsjApuDrQF2boVWPMFB5tJwuL5saflKZSiU1GQZdDdcmcKFK6j5LAsOhUFn3m9MDEM5tlsKDObYY/zouMJQYFWWl5useCQpv1ZxHGGJqtFsTAMMhkGDQYdCXt4HrXdPBc9JfeMiluUlZURAP0rUutEyoyFUcHN5ubmfsvR//lYxGW+bP4hZFhi3382ybIhdzAAXYG0ZJKvYqVTUfC5z4dclgUPoITndbmwLQyDIkFAJsOgVpaxLRBISYn5aJNpwPaEieLkODR124pEJfdWfc5h377kxnY4HGhtbdVhlYczb968TEKI/lmOvZASY0EI4XiezzZCQq+/eIXXC7ywLCpwE9/xVaMsw2XQFmFfKJR0hmMs1EkSNvr9mGQ2Y5LFglyex36d7m7RqtLJZjNmW60QGQZf+HyGp5lbGQYiIV0GV08YQmBhGPg1Y5FhUXDBnIg3mqzkXlZWliF1ItOnTxc9Hk9Kgpyp8izGTpw4UffbjiRJYPvZcy9fRtHpZTB7Qgsmjogvi65FUeAwwFhIlKJdUZBrsFexLxTCvnAYs2w2ZGlzjRFF7AuF+j3ZiJUDkoQcloVN+/2PEkWMNpmwzuc7oleI3gwTRVQZ5F3kat5FlCXRrcizNCnJvczMTEOMRXl5OSilKQlypspYFI0ZM0b3DXpnZyf6UtvqLnBz4/nxeRUSpSCAIaXo1eEwCjX9TKOoCoVQL8uYabFA6DYPTwhGiiK+TfIIUqIUe0MhjOkRc3FxHCabzfjKYIORy7JoUxRD8kdyehiL06a2It8RwJ4qFmvXJj6uzWZDZ2f8rSYGIisrC4QQ/SXneiFVxsJTUlKiu7JPR0cH+mp7uG4dsKWSgzMziB/MbYxr3GZZRo5BW5BaSepXOSpZGiQJNZKE6RZLr/UZRTyPVkU54vgzHnYGgxjRR1cxO8dhktmMDQaK2BBC4OZ51BsQMMxiGHQoSlfcIiK5FzlGTSbngmVZUEoNaRPAcZxAUtCMJSXGwuFwjCwoKND96uvo6OjTs4gqd1919iGIQnxf2lZFgd2AbUJQVUGBhEu3B8KvqtgeDOKEPgwFcHjdSCJ4FQXNioLifgyeg+MwTBCwJRBIaI5Y8PA8ag04FSGEQGQYhLoZumhP1BdfTk5yz2azGVJUZrfbKQBDWoB2JyXGwmKxjMjP11+9vLOzs1fPorkZeOkVAkIorl8Uf15+h6IYkrZcL8twG+RVUErxdSCAiWbzgHUsDo4DT0hCd+ZYpfKKtazUWoOSqDIZBj5FMUQVLFPzLqKUDvdj2qg2tHcwePPNxMfNyMgwZCuiCT71X3KtA6k6DSkaqHw8ESRJ6lVC75l/UYTCDM6a1ojhnvhvBQFVhcUAr87IE5ZqSYKNYWLePk0wmbAjFIrruLNBksASEvMcZZrMnx4B1Z4QTbLPiFORTJZFR4/twnfp34l7M2azGQEDvK3i4mIBx4qxkGXZrbexiO4pe97hVPW7rujxKncDkToHhhDdA5BUS/LKMGALolKK3aEQxsVxHNubJP5Ac+wIheKSyhO12pR9Rp1csKwhTYoyWfaItgoXn94IjlWx8kMW9fF/rQBEeooEDahvGTZsmAXHirEghFhMOmcryrIMrpc73IcfAnuqWBTn+rFwZnPc43pV1ZAL2q+qsDCMIacgByUJHp6PuzajN0n8vqgKh5GXQAuEEkFAjSR1BTsPNjTg1FtvxfglS1B6xRX4m9a+vKWjA/OXLsXoSy/F/KVL0RqDu57DcWjucVErioKp116Lc+6INBzfV1eHmTfcgNGXXoof3XsvwjFsizIYBt5uv5M2rxc3/OXXMPEfQVEIfv+7fWhpacH8+fMxevRozJ8/P6aEq+7G4i9/+QtKS0tRVlaGiy++GMFgEPv27cPMmTMxevRo/OhHP0I4RkNeWFgoZGVlDY/pxUlguLEghBCO43TfqAcCAZjNR+r+RgVurju3DomEHQKqakiT4XZVNSxj80A4nFDlKksIxphMA2pdhpJogcBq3dSjuhocy+LBG27Ajueew7rHHsOjb7yB7VVV+OO//43Ty8uxa9kynF5ejj/++98Djm1imCMM3d9efRXji4u7/n3744/j1osuwq5ly2DPyMDT774b05q7b89+/vDDOGvGDDx3RyTu9t+P8/HHP/4Rp59+Onbt2oXTTz8df/zjHwccN7oNqampwd///nds2LABlZWVUBQFK1aswO23345bb70Vu3btgt1ux9NPPz3gmEBE69Nms42M6cVJkArPwp6Tk6P7pjUYDKKnt3LwIPDWuyw4VsXV30vMVzTKWHQoCjIMMBYdigJBi+AnQj7HwasoaO9n7/9NKITRSbRAKO6mROXJyUH5mDEAgAyLBeOLi1HT1IQ31q7FkjPPBAAsOfNMvP755zGNLXYzGNWNjXhn3Tpc873vAYhs/T7ZvBkXzpv33bhr1sQ0LtEMRofPh1UVFbh64UJ878Rm2K1hbN0u4qWXvsGSJZHGYEuWLMHrr78+4Jgcx0HWtk2yLCMQCECWZfj9fng8HnzyySe48MIL4xoTiAjsMAxTPPArkyMVxsJTWFiou+8dCoWOMBZPPq5CVQl+MKcebkdiykpBSmEyYKvQqarINMAIHZIk5CdxwkIIQanZjMo+pOs6tJyMgiTmMDMMVOCI5s1Vhw5h8+7dmDl+POpbWuDRanw8OTloiLGOIoNhuoKRtzzyCB64/vou0ebmjg5k22zgNCNd6HSiJsZScZEQhCjF3ro6OLOzceX99+PEn16DPMcHAIC6uvldmq8ejwcNMfQOiG5BCwoKsHTpUhQXF8Pj8SArKwvTpk1DdnZ219a6sLAw5m7sHo8HiqIcEzGLnLy8PN1vqbIsHyajJ0nAU0/FL3DTk6CqGpIHYZTH0qgVvCVDNsvCyjCo6xEspJSiMhhEmQ6Sf06OQ1M378UbCOAH99yDv/70p8hMorzdwjAIqCre/uILuLKzMW3sdwWYvRm/WD+HWRtXVhRs2rkTN5x7LjY/+SQmjYx4JpJ0UcKSey0tLXjjjTewb98+1NbWwufz4b333kt4rRkZGVAURf/Cqx4M+O0lhCiEkK8JIdsIIVsIIb+Is7kJbzKZdL9KVFU9zFi88QZQV89iQlEH5k5uT3hcidLDUqT1QqVUd3VwSinClOpi3MabTNjZo5vZIVmGmRBdYi0Olu1SG5dkGT+45x4sPuMMXDB3LgAgz+FAXXMkIF3X3AyX3R7TuCZCEFRVfF5ZiTfXrsWwH/8YP77vPnyyeTNueeQRtHm9kDUjVd3YiPwBGmZH4QmBRCkKnU4UOp2YOWECAOCn5+XDKu4HpW68+GJE/aqurm5AWccoDMPgww8/xPDhw+F0OsHzPC644AKsXbsWbW1tXduU6upqxJOblIhiPiHkfEIIJYSMi2mOGF4ToJROoZSWApgPYCGA/4ljTRzP87pffYqiHGYsooHNnyyKT+DmiHEB6O0GGaVMHaRUN29FZBgUCgL2aMFOhVJ8GwxivE6nWBksC6+qglKKqx94AONLSvCLH/6w6/lzZ83Cc++/DwB47v33sWjWrJjGNTEMgpTiD9dei+qXX0bVihVYcc89OG3qVCy/6y6cOnUqXvnss+/GnT07pnFZRL4LbocDRS4Xvj1wAADwyeZNmDo6UiTywP0R1e7nnnsOixYtim1clkVhYSHWrVsHv98PSik+/vhjTJgwAaeeeipe0U6H4hkTiBwkxPzi77gYwBoAP47lxXF90yilDQCuA3BTHIvjeJ7X3bNQFAUMw2D5cqCgAPjkMw4EFGYxudx7xQAPQAUMEYfxacexejFCEFArSQioKvaEQigQBN22ZCZCENA8gBc+/BCfbN6MKddcgynXXIN3163Dry6+GB9u2IDRl16KDzdswK8uia1/DktIv1mc9193HR56+WWMWrwYzR0duHrhwrjHffjmm7H4d7/DpKuvxte7d+OxWyMtJyq2loIQijvuWIrm5vtiG5dlMW3aNFx44YUoLy/HxIkToaoqrrvuOtx///146KGHMGrUKDQ3N+PqOOS54jUWhBAbgNkArkaMxiLuzS6ldK+2DXEBiOXIwTBj8frrFtx2G+D3a2sDwc8fGQ2zScXiMxJrVqlA/0COCv29FSCSQNZbMVeiMIRgnMmEykAAPlXFyTrqj0S/y3MmTgT97397fc3HDz0U97gsIr/f7pwyZQpO0YSWRuTn46t//COpcaeMGoUNjz/e9dyNfx0FgAKI/u45/OtfHEQReOyxAcZlWSiKgnvvvRf33nvvYc+NGDECX331VdxrBRLyLM4DsJJSupMQ0kIIKaeUburvDYleF/EsjOM4Tvfbqqqq+N3vrF2GIoo/xOLOp0YkPjCluidOqVpWqN4olOpuhPI4DodkGdkMo7uH1W5AxaVEKaoNqD9pkGUc7CMp6om38tHbJfDEEwOPW1tba0h9SHV1dbynIRcDWKH9fYX2736J27MghIxA5AYc661bqa2tFT799NN4p+qXSHLLxF6fO9Ag4lOvN6FxO1UV/+3s1NVgROX2E11TX0iUQqFU1+pLWdPy2C/LONjeHtddIRbebk88+Nwb0fu73uNGzVpv4ypq778VRaF4++13+h2XEIL169frfkMaNmxYzEUnhJAcAKcBKCOEUEQcKUoI+SXtJ8AWl7EghDgB/BPAI/0N2gPZbrcHTjnllN6FJxJk+/btKChQUV195L212BXCKQm60Ku8Xsy2WnW9qyqU4nOfD3N1lhVslGUckiRM7CWTNRGots4ZNhv2h8PIZlndmkFTSvGZ14tT+tAfSZR2RcHeUAhT+2kFkQi7QyGIhPT6+RkCqL18+1mW4Jxzzul33HXr1mHy5Mm9Zh8nw09+8pN4BD4vBPA8pfT66AOEkM8AzAGwuq83xbINMUePTgF8BOADAPcO8J7uyJIk6X4cwLIsbr+9Az2/IwKn4nfX7E18XETcJj1hAEPEbC1a0FAvqiUJWVpXsbEmE3br2M0sRKkhfUVkAwLSQN+BbkUBMsy9b3uuuy6GcXuc4ulFnKI6FwP4vx6PvQqg36jygJ4FpTTZTyZJkqT7ZpVlWSxa5IXdbseddwL790cez8sO4pLTEwtuAt2i4Dp+AY0SMbIwjG7ydbJWuTpbS5ASCMEwQcDOOCtN+8KoAr0QpRCNyItB70Hplz51od0vwGZVEQgyUJSImtZ11w0c3ASOzA/Sizg8fVBKT+nlsb8P9L5UZHDKoVDIEGOhqioWLwaqqiItCvOcCg42WbBma+KN2qPJOHoTrTXQe0xWp/XuCoUwrEdXsWGCgEZZhk8Hg9SqKF3CwXpiVMatROkRtTCKAvzvs0UAgL/8hUCWI1qvshyboYiMoSSUQBUDhvdhSIWxaGtubtZdoYRl2a5sNwAQBOC66yL/uY+8mniafDQjUG9MhCBogBHqqUadCH5VRYMso6TH/pxEu5npINiiR1p6bwRUFWYDPIve0vNf/syFHdUZGFas4PIlic+pt6cZCARACDFOw1AjFcai7uDBg7pffaIoItSjtPr6GxiwLMVrn7tQ05hYYC6aEag3GVpXML3J4zjUJXl0uE3rudrb8W70Am9MwiCFKYWkY7ZpdzpV1ZBq3lCPgkJFAe57JuJV/PpOBgb1sk6Iuro6cByXeEFUjKTCWDQ1NjbqPk9vqkMFBcD556qQFQZPvOVOaFwzwxjiWWR2q47UE7um6pToViTagau/u36p2YztwWDC26jqcNgwRfOAqhpSJdwzN+aVz5zYUZ2BkiIFS65IbL6exY96UVdXB0rpQd0H7oHhxoJSqobDYd21z/rSM7zp55H/jMffykdYiv8/1UQIAkaIwLJsv5oRiUIIQYEg9JlA1B+UUmwPBlE6wDGelWHg5DjsT3COgwa1PwhrGaxGJNF1H1NVgfueTd6r6E2DRQ9qa2vh9/sTPwKMkZTI6qmqGoxVIixWeJ7vtdHs3LlA2XgZ9W0mvLrKGfe4NoO2CxkMg85u/Sj0ZJggYH84HLfS9X5JQi7HwRrD9mCMKKIqHEY4zjlqJAkOlk1YnKc/WmTZkK5xXlU97HfyymdObD+YieJCBVdcmbhh6kvdLVlqamrklpaWY8NY8DxfX5+oymkf9HU3IQS46eaId/HIq/FvRQTtdEHvi5pE+2gasBXhteSh3XEI40qUYp+mgBULnNaiMJ5uZop2HBvrHPHSJMuGtIHsUJQuoSK9vArAOM9i//79PgC1ug/cg5QYC0ppdV1dne7jchzXq3ex+FKCrEwVa3c4sGln/FmTRgU5czkOjQZ4LUCkYrRelmP2ir4NBjGyj65ifVHI82iLo5vZN8EginWsXCcz2OoAACAASURBVO1Js0H9aDtUtatvzKurnNh2IBNFBQquvCq57U4gEDDEWFRVVYUB6H+B9SAlxiIUCu0zwlj01T/SZgOuvCLy90dfi/8YtWeTGb1w83zSJxd9wRCCSWYzNgcCA25HOhUFrYqCojjjCNFuZpXB4ICeV6Mso01REhISjgWfqkIgxJB+tJ1akylVBe7VTkDuvCv5ExCv19tnu81kqK6uVnGsGIvm5uY9NTU1uvvfmZmZfVbw3XhT5KP9+5M8NLfHd/fJ1hrv6o2VYSBpx4hGkM2yKBYEfN2HnmaUWLuK9YaD4yAQgvp+jlJ9qorKQADTLBbDslfrktQe7QtKKfxa7sZrq/XzKoBIBz2bzvVBANDU1MQAiL/vRZykKsBZo+2rdKW/NvajRwNnzZcRlDj86934Yhc9O2nriZvjDGvpB0SCnSIh2NrH3b9eksATkpT7PsFkwjd9HKX6VRXrfT5MtVgM234AkbaIbgODm5SSLq9Cj7wKVVMJM+LoNBwOy5RS49rWa6Sqi3rN7t27dW/F1J+xAICbfh75Mj32ugfxOAomzQMwoo9mkSDggM4nQz0pNZlAAFT0uKAT6SrWG2aGQT7PY2+Pz9GpKPjK58Mks9mwHikA0KYoMCfR/qA/mhUFuRyH11Y7Ubk/E4X5+ngVPp/PEK9Ck+bTv9tyL6TKWOyoqKjQfVBBEBAOh/t0uc86CxhRoqCqwYp3v4xNqDWKUX00zQwDkRBDxo5CCEGZyQQLw+ALn6+rr8a+cBgejtMlk3KkKKK6WzezQ5KEjX4/yi0WQ4KO3akKhVBi4AmLg+EOy9bUY6qOjg5D4hUVFRVgWXaL7gP3QqpOQ4Jer9fXMz1bD/rrH8my38UuHn0tvq1ILssmleLcH8NFEXsN6v8ZhRCC0aKI0aKItT4fqkIhHAiFEuoq1hvRbmaVgQA2+/3YHw5jltVqSPf57oRUFW2KAqcxlZvoVBR8tDYPWzWv4qqr9Ym5dHR0IDMzU5exurN+/Xq5sbHxY90H7oVUeRbgOK5i69atuo/rcDjQ0tLS5/NXXkVgNql4f6MTOw/GnhDj4vl+g3jJkMuy8KmqLtWcA+Hiecy22bAnHAbV0aORKYVPUVAny7AyDGZYLIboVfRkTziMEaJoSOC0VVGQSdiuytI7fq2PVwFEeoU4HA59BuvGZ5991hYKhdbrPnAvpMxYNDc3f7x+/Xrdfe/c3Fw09dNlyuEAFl8S2aY89nrsx6g8IRAJgdegFO3RoohdBnTU7o1o/cQJZjP2hsNY7fVifzgc96kMpRQdioLKQACrvV4QQjDLajXMA+tJWFXRYFDqOBAJmm5ZX4CKqiwUeBRcfY0+BklRFMiyDNGArdPmzZspAP3vwr2QMmMRCAS+XLVqVZve42ZnZw/YwfqnP4u4rM+854E3ELv76uF5w04u8jgOXlU1JJ+jO5RSVAYCKDObkclxmG6x4ASLBSFVxTqfD6u9XmwLBnEgHEaLLMOrKAiqKvza2hokCXtCIWzy+/Gp14tvgkHkcBzm2WwYJYpwcBxsLKurDmhffBsKYaQoGiJ+TClFfVjG318YBkBfr6K1tRX2GJsmxUMgEIDf7/dSSo3d02qkzFgAqNiwYYMhuhY8z/cZtwCAKVOAOSfJ6AjwWPZBbJ2jAMCjKV0bQTTBaVsMCU7JUCfLsLLsYcIzZobBGJMJJ9tsmGm1IpdlEdYKvr4JhfB1IICtgQB2hUJolGVwhGC4IOAUmw0zrFZ4eP6wC3acKB7RzUxvOhUFbYpimFfRpijYvD4fW/bp61UAQFNTE3Jzc3UbL0pFRQU4jvta94H7IGXGglIa8Hq9fiOCnLm5uWhu7j8n5ac3RyL0j7zmQazfaUE7uTDq7m/nOIiEHNFjVC+6uor1c4sUCEEez2OUKGKy2YwTLBacaLViptWKaRYLSs1mlAgC7BzXZ5xAZBgUx1mbEg+UUmxNIpEsFqpCEp799ygAwK/uYKBnVnZzczNyYmybGA9acPMj3Qfug1R6FuB5fmtlZaXu4+bm5qKxsbHf11xwAeB2Kdh2IBOfbcmOeexhgoAqA/MiykwmfBsMdh1B6snuUAhFgmBIPkJPhgsC6rRuZnqzPxxGBsMYdiQrU4q31+Zi274s5LsVXHOtfgZJlmXD4hWrVq1KWXATSLGxaGpqMiTIabfb0dra2q87LwjA9T+JfNx4qlFdHIdmWdZN5fqIdTEMxplMqNB5OxJQVdRJEkakSNKJIQTjTSZs1zlo61NVVIXDuvVc7Y2DYQn/+c8YAPp7FfX19TE3TY6XjRs3piy4CaTYWBgV5GQYBna7fcCtyHXXE3Dc/2/vzMOjqu/9//6e2RdIJsskTBISQgiBDGGTyipabS120S6iT7ku/d2rFRH3WlvuVWv1+lMrv94q4rXV1iVSsEXF5SlWqwICCQECZCOQZbLPksk2+1m+vz9mJgTIMknOmUnCvJ5nnoeHTM73m+TM+3y+n5Xi/YNGNNsiU3pCCEwKBVolTNGeoVBAjmB/CbGoCg01lsIZOBRpCgVYSuEU6VjFU4pjHg+KNBpJCsaA4BFnx34DqhsSMCONxx13irtOe3v7qKahR4rP54PH43FTSqMTUkOUxQLA8QMHDghSOPRMJhNGqmw1mYAf3yCAFxj87weRWxfZoaOIlI7IIo0GTYEAukT4oDk5DiylSJPIGTgcZhGdthU+HzIUCkkzQh0cjzd3zAEgvlXB8zxcLpckyVj79+8HIWSf6BcehqiKBaXUTymtqampEf3a4XyLkW7ScNu9Vz+aAX8gsqeImmFgkMkkc0QCwYzIy7RalHu94zr3U0r7q0pjgV4mg0EmQ/M4raSG0IAjqUrcw7y+PwGn6xMlsSpsNhtSU1Mlccr+9a9/7Wpvb39T9AsPQ7QtC9hstr+89957orctZxgGCQkJI+ZcrFoFLDRzsPeq8e5XkZ8l56hUOOv3S2pdaBkGCzUalHo8o25fF6aZZZEok0nS8TpS5qrVqPP7x1yK38ayaGNZLNJoJIt+AEAny+HPxeesCrE73rW3t2PGjLGPpRgKSin27t3LYZhRg1IQdbEIBAIfvvPOO+JOCA5hMpnQ0tIy7HvG2nZPwzBIkMkkSwEPkySXI1+lQqnbPWqnKkcp6vx+zI2RVRFGQQhmqVSoHUMo1c5xOOP34xsiz5sdjLBVkW4U36rgOA49PT2SJGOdOnUKhJCTlFJpy5cvIOpiQSm1O53OzpFCnWPBaDSis7MT/Ah5ET/dQJCYIKDktAFHaiKvBJyjUuG03y/J3NKBzFAokKNU4rDbPaqnc63fj1lKJZRRdGoORbZCgU6Og3sUOSo2lkWVz4fLtdpRtfsbC3aWw2sSWhWtra0wmUySWEZ///vfPVar9S+iX3gEoi4WAODz+XZ8/PHHoodQGYaByWRCa2vrsO/TaoF//z/Bf4+mGlXLMDCOsSX+aMlUKpGrUuHwgBLz4XALAuyDTBWLFeFpZhURhlLbQ9mjyyVumgMEzfg/7Z/eb1Xc+XPxP9BNTU3Izs4W/boAsGvXLjfLsp9IcvFhiIlYdHV1vfvWW28NXSo6DmbOnAlLeEryMGzcxIAQir9+mQ57d+RRgzljbIk/FkwKBeaqVDjkdo+YRVrp9Uqa4TgWUuRyMITANszRjVKKM34/GgIBrNDpopJA1hhgUfxOMK/il4+Kb1V0d3dDpVJJ0py3vb0dvb29VkqpJJ+f4YiJWACoqaysDAxXzzFWNBoNlEolenp6hn3f7NnAddfy8LMyvPZx5NbFWFrijwejQoGlWi2OeTxDNvsNV32mSNx0ZiwUqtWoHqIFH0cpjnu98AgClkfh6AEERyDs+DoBlXWJSEvl8fO7xF/TYrEgJydH9OsCwJ49ezi32/2OJBcfgZiIBaWUEkL+8eWXX0py/ZycHDQ2No74vnDbve2jbLuXqVCgl+dFyYmIhGkyGVbqdGgKBHDygu7dQoRTxWJF+Oh2Ycp8D8/ja7cbyXI5iqKYPFbh8WLnDumsCpZl0dXVhdTU0Q+4ioTi4uKunp6ev0ly8RGIlWWBjo6Ot3fs2DF8nHOMGI1GdHd3XzQ4+UK+/W0gbxaPJocWHx2KvNCHEIKFGg1OSFxpORBlqMGMnmFwwO3uFypLIABjhFPFYsUclQqWQAABQYAQOnaUe71YEipSi9bRycqy+OJIKk6eNUhmVTQ2NiIrK0uSn8nj8eDMmTM+SukZ0S8eAbG8ww58+umnAbHHGgLBD3Nubi7Onj077PsYBti0OVwvMrp4uF4mw0yFAjVROo4AoZ9LpcKS0KDico9nVFPFYoU81Oyn3OvFfrcbAqVYrdNFNRckQCkqvT68E6osfeSXDLRacdfgOA4tLS2SHUE++OADQRCE3ZJcPAJiJhaUUo5S+t6ePXsk6S2XkZEBu92OkcTo9p8RaDUCPitPQbVldHfPLKUSPYKAzigdR8KEjyUeQQAHjGnOaTRx8TzaWRYOjsNclQpz1WrJcygu5JTXi5aTGTh6xgBjCo+7Nkrjq8jMzJSk3T8AbN26tdNms/1BkotHQExtV6vV+v9eeOEFSYajMAyDWbNmoa6ubtj3JSYCt/xbqO3ee6OzLgghWKTR4KTXC18U+mkOpE8QwAO4Sq+HAGCfyzWurEkp6OV5HPd4cNzrxSyVCit0OtRLXGMzGJZAAKDAtrdmAZDGquB5Hk1NTZg1a5a4Fw5RV1eH1tbWFkqp5AOQhyKmYkEprbVYLO2ROCPHQlZWFjo6OgadhzqQcNu9v+xNR697dE8FLcOgUKPBUY9H8mStMAPrPxQMgzkqFVbr9aAADrhcqPR6JW/XNxQCpWhnWRxyu1Hl8yFDqcRqnQ4pcjkMcjnUhEjWfWwwujgOlkAA7acyUFornVXR1NQEk8kEuUQRqZdeeqnP4XA8K8nFIyTmXjGn0/n89u3bJUn/DlsXI/kuFiwArljFweVT4K1P00a9jlEuR6pcjuoo+S+sHAfVBVPFFKGQ7lq9HobQXva5XDjr96OP5yV9mvOUwsayOOH14iuXC06Og1mtxnKdDsYLOmzNDzX7icaxyS8IOOH1YolGi9/+eSYA4BePEOh04q7DcRwaGxuRm5sr7oVDsCyLnTt3eliWfU+SBSIk5mLh9/v/9tZbb3mkcHQCwSQtm80Gj8cz7PvCYdTRtN0byByVCi5BQLPE2Z0CpagJ9aoYDCbUf+NynQ6Xa7WQE4Iqnw9fulw44fWiKRBA7zjFg6UUjlANR7jpr5XjYFIocKVej0KNZkjnpZphkKFUXjTNTGx4SnHU68U8tRoHjqagtNaA1GQeG+8W/5Y/e/YssrOzoZCoJcDu3bt5nud3R7sW5EJItM+Pg2E0Gv/nhRde2HTLLbdI4hmy2+1obGzEsmXLhnwPywI5M3m0dcjw2e/KcfXS0ffo4SjFIbcbc1UqGCW6cc6GalPyR5kdKFCKrtD09G6eD444IARaQqBhGCgJgSL06v8eoH+Qsz8054SlFDJCkBAqRU8aQ9iWpxT7XS4s1+kkSe2mlKLM60WKTIYcpQorNi5EyWkDnn9OwMO/EHc9j8eDI0eOYM2aNWAkCl8XFRXZT506tYxSOnJqsoTE3LIAALvd/twzzzzTJZVwpaamQhCEYeeLKBToP8uONowaRk4IvqHVosrnkyRhyxeyXGaPIVTKEIJkuRx5KhUu02px5bRpWKvTwazRYIZCgWkyGWSEIEBp/4unNHjckcmQrVRiWej71uj1KNJokKVUjim/Q0YI5oYyO8WGUooKnw96hsEslQqfHjGg5LR0VkVVVRXmzZsnmVCUlZXB4XBUxloogAkiFpTS1u7u7mOHDx+WbA2z2Yyqqqphze877mSgUFDsOZwKS8fYchdUDINlOh3KvV70iexkrPH5RA07EkKgZRikyOUwKRTIVioxW6Xqf+WqVMhSKpGmUMAgl4s6cSxdLoeXUtFF9UyoaU6BSgVKgSdel85XEa5wlqrHJgA89dRTzvb29sckW2AUTAixAID29vbHn3zySUnCqACg0+mQkpIybBp4ejpw448ECJTBKx+MvWmJjmGwVKtFmccjWlSim+fhFgTMmID1H2MhPLxZrBZ8NDT2oFcQsDDUNOefZQYcPm1AShKPuzeJe6sLgoDKykoUFhaKet2BtLe3o6SkxAnggGSLjIIJIxaU0sPl5eWtVVVVkq2Rn58Pi8UCt3voCfXhtnt//HgGfIGx/3qmy2S4TKvFUY9n3PNFKaWoDE0Vm0hVpeNlukyG6TLZuJshU0pR7ffDLQhYqtGAIURyq+LMmTNIT0+HXq8X98IDePzxx3t7enqeoBPBsYgJJBYA0NHRsXHz5s2Sld7K5XIsWLAA5eXlQz7Nli8Hlizk0Nmnws5/ja8YaJpMhm9otTju8Yyr43Uby0J/wVSxqUKBStV/dBgLYR8FSykWDxDTf5YZcKhGGquip6cHNpsNeXl5ol53II2NjdizZ4/N6/XukGyRUTKhxIJSerCqqqry0KFDkq2RnJyMxMRENDQ0DPp1Qs6FUV/8+9jCqAPRyWS4XKfDKZ8PrWMIF3KUotbvR8EEr/8YK0qGQfYYp5lxlOKIxwMZISga0MuDUuA3fw5OQn/4FwRiPvwFQUB5eTkWLVokmVMTAB588MEuu91+D6U0uqnBwzChxAIIWhebNm3qlNLyKigoQHNzM1yuwXPBbr4ZSErkcfRsIkqrI2+7NxRahsFKnQ7NLIvTozyj1/n9mBmlqWKxIkephJXj4BlFyrxXEHDQ7Ua6QoH5FzT9+eyoAQerk5Bs4LHpHnF/b6dPn0ZGRgamTRv/fTEUJ0+exMGDBy2CIHwq2SJjYMLdgZTSyra2tgOffPKJZIoqk8lQVFSE8vJyCIPcoBoN8B+hwbgv7RanO7OCEFyu1SIQShaKxOz2CgLaOU7ydvixhiEE81SqiKeZdXEcDrvdKFSrMfOC342UVoXT6URnZydmz54t3kUHYfPmzZ1Wq/WuieKrCDPhxAIArFbrfQ888IBzsA+yWBgMBqSlpaGysnLQr4fb7u36Kg22LnESrAghWKDRIFUuxwG3Gz0jtcrz+TBfpYrqVLFYYVQowFM6bAVvuAVfhc+Hb+h0SB4kMvT5MQO+rhLfqvD7/Thx4gSWLFkiqZN5//79qK2tPUUpLZFskTEyIcWCUmrp6el5v7i4WLqZgQDy8vLg9XoHHR+QkwN8/zoeAU6GP30Uedu9SMhWKrFUo8EJrxd1Q8wiCc9XlSoTdCJSOEwo1ScIOOzxICAIWKXTDZoMNtCqeOhhArFOCoIgoKysDIWFhdCKXa46AEop7rnnns6Ojo6Nki0yDiakWACAzWb71ZYtW7qlqhkBgk/6xYsX4+zZs+jt7b3o6/1t9z6YAY4X92kyTSbDqlBPihKP57zzeriq1Bzj+R/RRi+TIVkmQ9OAUCqlFK2hKtbZSiUKQ6HRwfjXsUQcqExCUiKPezaLd2tXV1cjJSVF0uQrANizZ49gs9m+oJSKP7JPBCasWFBKHR6P50/btm2TtJRToVBgyZIlOHbs2EWl7FdfDczN49DSqcWeryNvuxcpstCxJC80VChc99HEskiSyaCfgqHSkchXq1Ef6ssRFlIby2KVTjeslRW0KoJ5FWJaFW1tbXC5XMjPzxfngkPA8zweeughZ0dHx/2SLjQOJqxYAEBnZ+fTzz33XPdwNR1iMH36dMyZMwdHjx49z+HJMMDd94x+etloSZHLsUavDxZYud2oDaV1X4ooCEGOUokStxulHg/yVCos1mpHTDX/4ngi9otsVfT09KC2tlZyPwUAvPLKK/6+vr5dlNLhh97EkAktFpRSd3d396bbb79dksa+A8nIyEBycjJOnDhx3pn5ttsJdFoBX5xMQWWDdOfVcHHVdIaBnBAc93hEry2Z6FBK0RQIoDEQgEcQsEStjmi8wcBszYceJhBjaLnb7caxY8dw2WWXSVZ6HqaxsRG//e1vbTab7RFJFxonE1osAMDr9e4uKys7+O6770reXikvLw9yuRzV1dX9/5eQANx6S1A8to2y7d5ocfE8+gQBV+r1mK1S4aTXi+MX+DOmIjTUXWuf240+nscqnQ5LtVpUR5io9WV50KowJAiiWBV+vx9HjhzB4sWLJU3nBoI/+8033+x0OBwbKKVD1yFMACa8WACA1Wq99b777nNIMR91IIQQmM1meDwe1Nefa3UYbrv35qfp6HFJ50eo9Pn6E4yS5XKs1OlgUihw1ONBmccTtTkl0YKnFJZAAPvcbtg4Dt/QalGo0UDJMEiWyyEjBLYI6kaeeD0cAcG4rQqO41BaWor58+cjMTFxfBeLgJdfftnf0NDwPsdxUZ2IPhYmhVhQSp1dXV0bo3EcCUdIOjo6+memFhYCV13Bwe1X4I29o2+7Fwk2lgVDyHlmNyEEaQoFVut0yFUqccbvx9cuF9pYdkJ38x4JryCgJtT2zxeaRrZQo4HmAr/EfLUaVSMMov6yPBH7KpJhSBCw+d7x3c7hEGlOTo7kkQ+g//hhtdlsmyVfTAQmhVgAgNfrff/o0aNf79y5U/LHq0wmw7Jly9DQ0NCfgxEOo27bbYLYpwIhVDVZOIRTk4T6bX5Dp8MirRZdHId9oTZ5To6LerfsscCG/BFfu1w45vFAyzC4Qq/HXLV6yFR2LcMgXS5HwzDh87BV8eBD47MqeJ5HaWkpjEYjsrKyxn6hCBEEATfddJPT4XD8lFI6fM/HCcKEaKsXKYSQpBkzZlSWl5enR0P5WZZFaWkpsrKyYDLNxKxsHi1tMux97gS+vUw8I6fe74ef0iH7ag4GpRR2jkMzy6KX55Eql8OoUCA51PFqIuAVBNg4DlaWhUcQMEOhQJZSCe0o6ly4UAu+lYMMTf6yPBFXPbAIidMFNDYxSEgY2z7DR4+MjAzJJp9fyIsvvuh76qmn3rZarXdEZUERmDSWBdB/HLnrtttuk/w4AgRzMC6//HK0traipaURG+8eX9u9wQgIAiyBwKinihFC+ocmX6HXI1UuRwfLYr/LhRK3G3V+P5wcF9Xjik8Q0M6yqPT58FXIgmApRYFajbUhK2I0QgGcm2ZWM4izM5yt+eBDGLNQsCyLkpISZGVlRU0oGhoa8PTTT9tsNtt9UVlQJCaVZREmPT19z+9///t1N998c1TaRvE8j7KyMhCShjWrs8FyQF1xCWbNGH++2EmvF0kyGTJFLBZz8Tw6Q815e3geBECCTAY9w0AXemkZZkwWCA3153SHGvi6BQG9oS5eKoaBIdTIN1kuF20qOqUUX7vdKNJoMD2UqPZVeQKufGDxuKyKQCCA0tJS5ObmwmQyibLXkRAEAStWrHCWlpb+gFL6dVQWFYlJ2aPNarXedv/991csW7bMJHUFIHDOh3Hs2DFce+10fPhREra/PwPPbRy8J0ak9PI8enkeC0ROwNKHsj/Dz0mOUvTyPFyCgC6eR0voWBB2HDKE9Hf3vvDjzeNch+/wg0U5QHQSZDJkKhTQMYxkiUuEEJg1GlT4fFih1YIQ0p+t+cCDY7Mq3G43jhw5goKCAqSnS5dwdyFPPfWU22Kx7JpsQgFMUssCAAghS/Ly8j49evRo8nQxsnAigFKKd9+14KabcmDQBdDyt8PQqsfm7aSU4pDHg3kqFQwx7qvJh6yFwUYfMsA5IYmxL+TpjxOw/c0CtNnUoCDQqAW0tTMYbYTT4XDg1KlTWLx4cVTCo2H27NnD3XHHHcdsNtsqSumki4NPKp/FQCilx2w22/0//OEPu6UsZR8IIQTr1+dg4QIfutxKvPH52NvudXAc1ITEXCiAYPaohmH6e2IOfOllMigltBoipfgzI/77xSK02jSgIfuH4wk+/nh017FYLKiursby5cujKhSVlZW4884722w227rJKBTAJBYLAOjp6Xm7oqLijUceeUSS8YdD8eDDwWPD1t0z4GBH/3fnQ52o51+i9R+jxetn8PD22fD4z0+IY1mCLVsiu0a4G7fNZsOKFSug0Wgk2OngdHZ24rvf/a7DarV+h1IqWY9ZqZm0x5AwhBDGaDT+a+vWrSs3bNgQleYPPh+QlcHD4ZTh5ecP4GqzC3NUqoifvmdCnv3RRkCmOixHUNusQUWDDpUNWlTUa1DRoEddhxYCHfy5RghGzHvxer04duwYUlJSkJ+fH1UriWVZrF69uuvUqVO3eTyeD6O2sATE3gYeJ5RSgRDy/QcffLC8oKAgd+nSpZKvqVYDd9xB8MyzwP5PcrHWfBKHPB4s0WhGHMfnEwS0BgJYI3HNwUSG54GGjqAoVNRrUVGnQWWjFqdb9WD5i9PpZTIKOaHguIs/5DNnDr9WW1sbTp8+jaKiIiQni99mYCQ2btzYW19f/4fJLhTAFLAswhBCcjMzMw8dOXLEGA3vdlMTMGsWhYwIaNpVAtl0Dyq8XsxXq5E2TJXicY8H6QoFZlwCHbAoBVrsqqAoNOhQUadBRb0W1S16eAMXP6cIocjN5mEuBMwLZSg0E5jNQH4+8Le/AXfeCQycb63RUPzxjwQbNly8Ns/zqKiogN/vx6JFi6CMQR/Tl19+2ffEE098ZrfbfzDR+mmOhSkjFgCgVCqvnjdv3q7S0tIkVRRM/B9dz+O9PTI8eXs9/uu2JvgFAce9XmgYBvPV6ovyDLo4DtV+f3/4b6pAKWDrUqCycYAoNGhRaZmGXu/gophp4mGeT2EuYmAuYlBYCMybh2GHARUXA1u2BIU6M1PA7bfX4je/mXvR79LpdOLUqVPIzs5GdnZ2TH7XX331Fb3xxhtr7Hb7UkqpN+obkIApJRYAkJyc/NDq1av/a/fu3QkyiTtNff45cM01gCnJi8adpVDIg7kIzSyLOr8fc9VqzJDLQQgZNLFoMtLVJ+8Xhcp6TdCv0DgNjr7BxTk1+XxRMJuB+fMx6nDnYJw8eRIGg6G/loNlWVRVVcHtKqbYBQAADlBJREFUdqOoqEjy8vKhqKmpwVVXXdXR0dFx2URuZjNappxYAIDRaPzdNddc8x9vv/12gpSDYCgF5s/lUHNGjl2PV+LGK8+V0PsFAZWhSVkLNBo4OQ5OnkdRFL3w48HtZVBlCVkK9ZqgMDTq0eocvAFQwnQBhQUCzAsIzAtlMJuD1bpSlvAEAgF8/fXXWL16NWw2G2pra5GXl4fMzMyYWW51dXVYu3atrbW19WpKaUVMNiERU1IsCCEkNTX1pe9973v/9tprr02X8sbZ9hLFPZsJrjB34qsXT130dTvHocLrhZ9SrNXpoJlgVoU/QHC6WXvO2VivQWWjDvXWwZ/KGnVQFArN50TBbAYyMoKRiWhTXV2N1tZWJCcno7CwMCa+iTAWiwVr1qyxNzc3X0spPR6zjUjElBQLoF8wXvvJT37yk23btk2TSjD6+oAMk4A+F4MTfzqCotkXNzuq8nrRJwjwCAJyVSpkKRRRnwXC8QRnWzXBkGS/X0GHM+068MLF1pdCQVEwhw9aCAtkQYvBHByRMBH0zuv14vTp0+jr60MgEMCKFSskbdM/Eq2trVi1apXDYrF8l1JaGrONSMiUFQsgKBhGo/Ht9evXf/8Pf/iDZIKxeROPl16W4c7rWvC/vzh73tc8goBSjwdX6HTgEcyxsHEc8lWqfn+GmAgCYLGqz+UqhEShukWPAHfxp5xhKPJmXRyBmDMHmIgBm0AggDNnzsDhcGDu3LlIS0uDw+FAY2Mjli1bFpM9tbS0YO3atQ6LxfJDjuMOxGQTUWBKiwXQn7T15+uvv/6GV155ZboUPoyamqAnX6vi0PLuYRimncvqPOLxIFuhOK+NvU8QcNrvRy/PY/YYRYNSoL1T2R+WrKxXo6Jeh8omPdz+wT/l2Zk8zIXnRyAKCoLjGic6fr8fDQ0NaG9vx+zZs5GVlXXe76ykpASzZ89GSkpKVPfV2NiIK6+80tHS0nI9x3EHo7p4lJnyYgH0H0leufbaa29+4403JBGMb32Tw2dfyLF14xk8sD7oAO/kOJz1+3H5EPFAtyCg3u9HJ8dhplKJmUol5IOIhqNHce74EPYrWKahyz34+TzdOHgEQsJZvpLR29uLuro69Pb2IicnB5mZmRgsyuV2u3H06FGsWbMmas7Ns2fP4pvf/Ka9ubn5OkppWVQWjSGXhFgA/YKxde3atT/bsWNHglzkAq4PPgBuuAGYne5CbXEZCAnOAFmi0Yw4LIgNNa6t6RbQ25aI7pZE1DaG/AqN02DtGbyGxJAgwDxfgLmIwFx0LgIRg0RFUaGUwm63o66uDoQQ5ObmIjU1dUQRqKqqglarRU5OjuR7rK6uxre+9S1ra2vrtZTSE5IvOAG4ZMQijNFo/E1+fv7mDz/80GAwGES7Ls8DxlQBzi4GBBQmow+bbzuNX17XfdF7vX4G1RZtMF+hXoOKOi0qGvVocgzuoNNpBZjnXRyBSE+PTQRCKvr6+tDc3Ayr1QqDwYDc3FyMpv0Ay7I4cOAAVq9eLemsj08//VS49dZbO6xW67cppYNP1p6CXHJiAQA6ne7HaWlpr3zyyScpBQUFolyzuBj42c8oWPbcp1ej4vH4rQ3ISfcHMxpHKIxSKSnm5fMwLwDmFAgwGm1ITGxBbq4c2dlZSE1NhZR5I7HA5/OhtbUVra2tUKlUyMzMRHp6+qBHjUhoampCb28vzGazyDsNWjxbt271Pvvss2fsdvu3KKU20ReZwFySYgEAhJAFaWlpn7z++uszrrvuunEHA3NyAIslsvfKZBT5s4NhSXPRuQjE7NnAhacjSim6u7vR3NyMzs5O6PV6GI1GpKWlQT0JS9zDP4/VaoXNZgPDMDCZTMjIyIAYKfqUUhw4cACLFi3CNBGdNH6/H7fffnvP559/vtdut99CKZVuYvcE5ZIVCwAghKSkpqbuvf/++wt+9atfacfjGGOYYITiYih+cB0fPD4sOFcYNZbPBaUUfX19sNlssFqt4HkeKSkpSElJQWJiYkwTkoaCUgqXy4Wuri7Y7Xb09vYiISEBaWlpSE1NlWTPTqcTtbW1WL58uSjX6+jowLp165xNTU3POJ3OF6ZCUdhYuKTFAgAIIQqj0fj6qlWrvv/OO+8kjPVpPZRlkZ0NNDaOa4tDwrIsHA4HnE4nurq6wHEcpk2bhsTERBgMBkybNk3yOZ0DoZTC6/Wip6cHXV1d6O7uht/vh16vh8FgQEpKChISEqISrTh69CgyMzORlja+oVDHjh3D9ddfb7darT8NBAKfibS9ScklLxZhkpKS7svIyHhs7969SWPp9FxcDNxxhwCv95xPQasFXn0Vg5ZQS4EgCP1P8a6uLrhcLnAcB4ZhoNPp+l8qlQpKpRIKhQJKpRLyCPI8BEFAIBAAy7JgWRaBQABerxdutxtutxteb7CwUqPRYPr06TAYDEhMTIzZUcnr9aKkpARXXHHFmP08O3bsYO+///4Wm832LUppnchbnHTExWIASqXyytTU1J27du0yrlq1alTfKwgCHnusBm++WYCWFgYzZwJPPx09oRgOjuPg8Xj6P9h+v7//Ax/+8I8EIQRKpbJfZBQKBTQaDXQ6HfR6PdShGa0TidOnT0Mul2O0HeBZlsWjjz7qeuutt47b7fbvUUp7JdripCIuFhdACMkxGo3vrV+/fvZzzz03LdJejXV1dWBZFmJFV+KMH57nsW/fPqxcuTJi5+mpU6ewfv36TofD8YrD4XicUspLvM1Jw9SKw4kApbTRZrMtLS4uftJsNjsOHz484vf4/X40NTUhLy8vCjuMEykymQz5+fmorq4e8b0sy+Kxxx5zX3PNNbU1NTVX2u32/4wLxfnExWIQKKWC0+n8XX19/fLrr7/+xL333tvn8w09faympgb5+fkQOys0zvgxmUxwu93o6ekZ8j0VFRVYuHBh5/bt2/9gs9nMU60PhVjExWIYKKV1Npttydtvv/3bwsJCR0lJyUXv6enpgcvlitr4uzijgxACs9mMioqKi6bNcxyHJ554wnP11VfXVldXf9Nut/+aUjqyA+cSJS4WIxCyMp6vr69f8YMf/ODkfffd129lUEpRUVGBwsLCCefci3OOhIQE6HQ6tLe39/9fZWUlFi5c2Llt27awNXEyhlucFMQdnKOAEMIkJSX9IjEx8eE//vGPyQUFBcRqtWLx4sWx3lqcEfD7/Th48CCWLl2K559/3v3qq6+22Wy2n8RFInLih+xRQCkVADxLCPnbhg0bXs7MzLzixRdfnHw515cgDMNg//793C233NLndruf7e7u3ho/coyOuGUxDgghS9PT01+57LLLcn//+98nRWOie5zRIQgCdu3axT/66KNOt9v9psPheDKeNzE24mIhAjKZ7OrU1NRt69atS3/mmWcSojHkKM7I/POf/6T33ntvZ1dX1ydWq/URSqk11nuazMTFQiQIIUSlUt2YmJj4/K233pq0ZcsWfUJCQqy3dUlSVlaGTZs2dTY1NZV2dHTcQymtj/WepgJxsRAZQohi+vTpP9dqtVs2b96ccPfdd2sSxZioE2dEjh8/jl//+tfO8vLyMx0dHXdRSstjvaepRFwsJIIQok1ISNioVqvvX7dunf7RRx9NnDt3bqy3NeXgOA7vv/++8NRTT3Xa7fbqtra2/6SU7o/1vqYicbGQGEIIwzDMurS0tN/k5ORkb9myJfk73/kOkXq04lTH4XDg1Vdf9W7fvt3Fsuz7Vqv1GUppQ6z3NZWJi0UUIYTMT09P/5VMJrv2tttu095111268JzOOCMjCAK++OILvPDCC47jx4/3ut3u/+nr63udUuqK9d4uBeJiMQSEEB7AwHmEf6WU/l+Rrq1Vq9U3GQyGh3Nzc1PvvffelHXr1hEx28BNJWpra7Fjxw7va6+95uI47sv29vbnABwVq2PVIH/rGyiljWJceyoRF4shIIS4KKWSj+EmhMxPTU39d7lcfkNWVta0DRs2JN5www2KmTNnSr30hIXjOBw6dAg7d+7s+eijjwIcx9V2dnb+2efz7ZTCiojW33qyExeLIYjFDUQImanT6X6UkJBwi1arzfrRj36kufHGG/VLliyZcl29L6S3txd79+6lxcXFnSUlJbxMJtvX2tr6BoB/UUq9Uq4dF4vIiIvFEAximj5DKd0ZxfWnMwzzbZPJ9DOe5y+76qqr5OvXr09atmzZlKhwZVkWVVVV+PLLLwPFxcU9zc3NLp7nd9vt9r8COBZKrY8KF/ytGyilP4zW2pOJuFgMwUR62hBC5ABWGI3GHysUijWCIGTMmjWLrFmzRrty5Ur90qVLYTKZJmzlK8uyqKysRFlZmbBv376u0tJSoaenx6tQKCo7Ozv/4fF43qeUNsVqfxPpbz2RiYvFEEzkG4gEVSETwFKj0bg2JCCZOTk5ZPXq1dqVK1fq8/LyMGPGDCQlJUVNRAKBADo6OtDW1oaTJ0/y+/bt6z5y5IjQ29vrVSgUFU6n819ut/swgHJKqTsqm4qAify3nkjExWIIJtsNFBKQDABLU1NTr1Cr1fMFQTDxPG+Qy+VKrVbLmEwmYebMmfKcnBxNVlaWJiMjgxiNRqhUKsjl8vNelFKwLAuO4/pffX19aG9vR2trK2exWNwWiyXQ1NREHQ4HYVmW5XneJ5fLbQBanE7nQY/HUwLgxEQShsGYbH/rWBEXiyEYxGfxD0rpo7Haz3ghhKgBpAOYAcCkVCozkpKS8hQKRRYhRAVAQSmVA1Ag2LpAAMARQlgALABOEIRej8dT73Q66wC0D3g5ouljEJu4WERGXCzixIkTEVM7HhcnThzRiItFnDhxIiIuFnHixImIuFjEiRMnIuJiESdOnIiIi0WcOHEiIi4WceLEiYi4WMSJEyci4mIRJ06ciPj/8hDjJu/kQykAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "radar_plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 练习\n",
    "# 测试数据，5次考试的平均值， 第一行是1班考试成绩，第二行是2班考试成绩， 自定义一个主题，画一个柱状图， 画一个饼图， 如1班和2班5次成绩比较， \n",
    "data = np.array([\n",
    "    [80, 84, 92, 100, 62],\n",
    "    [60, 100, 100, 93, 86],\n",
    "])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas 中的使用\n",
    "\n",
    "[参数说明](https://blog.csdn.net/claroja/article/details/73872066?utm_source=debugrun&utm_medium=referral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0,2*np.pi,100)          # 从0 到 2π  取100份\n",
    "df = pd.DataFrame(data={'sin':np.sin(x),'cos':np.cos(x)},index=x)   #创建DataFrame对象\n",
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.plot(title='title', fontsize=20, figsize=(8, 6), grid=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s = pd.Series(data=np.random.randint(0,10,size=5),index=list('abcde'))  \n",
    "s.plot(kind='barh')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame(np.random.randint(0,150,size=(20,3)),columns=['python','math','eng'])\n",
    "df.plot(kind='scatter',x='python',y='eng')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['php'] = df['python'].map(lambda x: x*0.9+np.random.randint(-10,10,1)[0])\n",
    "df.plot(kind='scatter',x='python',y='php')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 练习 录入数据， 用id 和 price 两个参数画一个柱状图 , 散点图\n",
    "wz_df = pd.read_csv('datas/waizi_v2.csv')\n",
    "wz_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "wz_df = wz_df[wz_df['type']=='合同外资金额']\n",
    "wz_df.plot(kind='???',x='???',y='???')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
